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Auteur principal:	Ivaniha, Oksana
Format:	Recurso digital
Langue:	anglais
Publié:	Zenodo 2026
Sujets:	atmosphere subtropical transport barriers transport diagnostics stratosphere dynamics
Accès en ligne:	https://doi.org/10.5281/zenodo.18418358
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File description This module provides a unified framework for diagnosing subtropical transport barriers (STBs) and tropical width in the stratosphere using long-lived tracers and transport diagnostics. It is designed to operate on gridded atmospheric datasets (NetCDF) handled via xarray, and supports both pressure-coordinate and potential-temperature (θ) analyses. The physical motivation for the code is that long-lived tracers such as N₂O, CH₄, and the Age of Air (AoA) are predominantly shaped by large-scale transport in the stratosphere. Their meridional gradients and spatial distributions therefore provide robust diagnostics of the Brewer–Dobson circulation (BDC) and the associated subtropical transport barriers. AoA is treated as a purely transport-controlled artificial tracer, allowing an integrated assessment of advection and mixing without chemical influences. Data handling and preprocessing The module includes utilities to: All input data must be read and preprocessed using the provided helper function: 'load_nc_xarray'. This step is mandatory. The function ensures: - consistent naming of dimensions and variables, - correct decoding of time coordinates (including non-standard calendars), - proper sorting of latitude, longitude, and vertical coordinates, - compatibility across different models and reanalysis products. Using raw xarray.open_dataset() without preprocessing is not supported and may lead to incorrect results. Tropical width and STB diagnostics The core routine (Tropical_width3D) computes southern and northern subtropical boundaries as a function of time and vertical level using multiple tracer-based metrics. Three primary methods are implemented: 1. Gradient Weighted Latitude (GWL) The GWL metric estimates STBs as the latitude of the strongest meridional tracer gradient, weighted by both the gradient magnitude and the cosine of latitude to account for spherical geometry. Rather than relying on a single local maximum in the gradient, this approach integrates information across the full latitudinal gradient structure, making it less sensitive to grid resolution, weak extrema, and noise. The method yields robust estimates of the southern (ϕₛ) and northern (ϕₙ) subtropical boundaries and closely follows the formulation of Davis & Rosenlof (2012) and Shah et al. (2020). 2. 1-Sigma metric The 1-Sigma method identifies the latitudinal extent of the tropical tracer reservoir by determining where the tracer concentration falls below one spatial standard deviation from the tropical mean. The mean and standard deviation are computed over a 70° latitude window centered on the tracer maximum, allowing for hemispheric asymmetries and seasonal shifts. This metric is sensitive to the chosen latitude window and therefore reflects changes in the overall width of the tropical tracer belt rather than localized gradients. 3. Probability Distribution Function (PDF) metric The PDF approach diagnoses STBs by identifying minima in the equal-area tracer concentration PDF, following Sparling (2000) and subsequent applications. These minima correspond to regions of reduced mixing that separate the tropical pipe from the midlatitude surf zone. PDFs are computed independently for each hemisphere using Gaussian kernel density estimation (KDE), with tracer values weighted by the cosine of latitude to emphasize dynamically relevant subtropical regions. This method captures transport barriers from a statistical rather than geographical perspective and complements gradient-based diagnostics. Additional capabilities A cross-value method identifies boundaries based on tracer isopleth crossings, using monotonic PCHIP interpolation. A gradient-extremum method applies Gaussian smoothing and derivative analysis to locate robust transport barriers. Support for non-zonal data includes longitude-by-longitude boundary detection followed by spherical averaging. Validation and visualization The function: Plot_width(...) is a helper function intended exclusively for validation and quality control. It provides a quick-look visualization by: - overlaying diagnosed STB latitudes on latitude–height cross sections, - comparing multiple diagnostic methods for the same time step, - identifying spurious boundary jumps, vertical inconsistencies, or unrealistic behavior. This function is not intended for producing publication-quality figures. It should be used only to verify that the diagnostics behave as expected in practice before applying them to large-scale analyses. A Jupyter notebook ('Evaluation of the subtropical boundaries.ipynb') is included in the repository, demonstrating: loading and preprocessing of the data, computation of STBs using Tropical_width3D, validation using Plot_width. The example uses monthly mean data, but all functions are fully compatible with daily data. No changes to the code are required to switch between monthly and daily temporal resolution.

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